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All Journal MAESTRO Kresna: Jurnal Riset dan Pengabdian Masyarakat OKTAL : Jurnal Ilmu Komputer dan Sains AMMA : Jurnal Pengabdian Masyarakat
Suwasti Broto
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Humanities Astronomy Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing Social Sciences

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PREDIKSI IRADIASI MATAHARI MENGGUNAKAN ALGORITMA ARTIFICIAL NEURAL NETWORK Fatahillah Al Mahfudz; Suwasti Broto; Akhmad Musafa
MAESTRO Vol 6 No No 2 (2023): Vol.6 No. 2. Oktober 2023
Publisher : FAKULTAS TEKNIK UNIVERSITAS BUDI LUHUR

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Abstract

Prediksi iradiasi matahari merupakan hal yang krusial dalam merancang dan mengembangkan sistem energi terbarukan dengan energi matahari. Dalam tugas akhir ini dilakukan prediksi iradiasi matahari dengan meggunakan algoritma Artificial Neural Network (ANN) dalam bentuk model sekuensial. Model Sequential ANN dilatih dengan dataset yang mencakup berbagai faktor cuaca seperti suhu, kelembaban, tekanan udara, serta data radiasi matahari historis. Proses pelatihan dimulai dengan membagi dataset menjadi data latih dan data uji dengan tiga variasi komposisi data latih dan uji yang berbeda (80%:20%), (75%:25%), dan (66%:34%). Model ANN yang dibuat terdiri dari empat lapisan, satu lapisan masukan, dua lapisan tersembunyi dengan jumlah neuron (32, 64), dan satu lapisan keluaran. Melalui iterasi berulang, model diperbarui menggunakan algoritma optimisasi Adaptive Moment Estimation (ADAM) untuk mengoptimalkan parameter. Model ANN diuji dengan tiga variabel masukan iradiasi matahari yang berbeda (Global Horizontal Irradiance, Diffuse Horizontal Irradiance, dan Direct Normal Irradiance). Hasil pengujian menunjukkan bahwa model Sequential ANN mampu menghasilkan prediksi iradiasi matahari dengan tingkat akurasi yang signifikan. Hasil prediksi menunjukkan Mean Absolute Error (MAE=0,0029) , Mean Absolute Percentage Error (MAPE=2,3289%), Root Mean Square Error (RMSE=0,0038), dan Mean Square Error (MSE=0,0001) pada komposisi data latih dan uji (80%:20%).
Rancang Bangun Pembangkit Listrik Picohidro Curah Hujan Pijar Nurofiq Pratama; Indra Riyanto; Suwasti Broto
MAESTRO Vol 6 No No 2 (2023): Vol.6 No. 2. Oktober 2023
Publisher : FAKULTAS TEKNIK UNIVERSITAS BUDI LUHUR

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Abstract

Indonesia has a fairly high rainfall of (2000-3000 mm per year) This has the potential to be used as an alternative energy source for power generation. In this final project, a picohydro power generation system was designed with energy sources derived from rainfall. The designed system consists of gutters with a height of 1 m, 1/2" pipe, YF-S201 water flow, Picohidro Generator, INA219 sensor, Arduino Mega 2560, RTC DS3231, LCD, I2C, Micro SD Card, and 5 watt dc lamp load. The way the system works is that when it rains, the water will be collected by gutters which then the water will flow through pipes connected to the water flow and generator. Water that passes through the water flow and generator will rotate the turbine so that it produces data on water discharge and electrical power. The INA219 sensor will read the current and voltage as well as the power generated from the generator with a 5 watt dc lamp load. Water discharge and power data will then be displayed on the LCD and stored on the SD Card. The designed system is tested by means of three test scenarios namely testing 1 single generator, 2 series connection generators, and 2 parallel connection generators. From the results of system testing, the highest data was obtained in testing 1 generator that produced 25.64 mW of power with a potential energy of 1.5384 Joules.
Co-Authors Achmad Rizky Arsanto Narendro DODY KURNIAWAN Faisal Adi Putra Tomyka Ode Fatahillah Al Mahfudz Fath, Nifty Fikri Hidayatulloh Hendryono Saputra Hilman Mustofa Indra Riyanto Inggit Musdinar Sayekti Sihing Yang Mawantu Jalu Nuralim Laksana, Eka Purwa Maulana Ifdil Hanafi Musafa, Akhmad Musodo, Krisna Adiyarta Nazori AZ Peby Wahyu Purnawan Pijar Nurofiq Pratama Ricky Palendra Riefky Rakadiansyah Ruwirohi, Jan Everhard Safwan Firas Sujono Sujono Tatang Wirawan Wisjhnuadji Tatang Wirawan Wisnuadji Yani Prabowo